Pandas Filtering Data
In [2]:
import pandas as pdhouses = pd.read_csv("data/kc_house_data.csv")titanic = pd.read_csv("data/titanic.csv")netflix = pd.read_csv("data/netflix_titles.csv", sep="|", index_col=0)
In [78]:
df = titanic.head()df.sex
Out[78]:
0 female
1 male
2 female
3 male
4 female
Name: sex, dtype: object
In [79]:
df.sex == 'female'
Out[79]:
0 True
1 False
2 True
3 False
4 True
Name: sex, dtype: bool
In [81]:
df[df.sex == 'female']
Out[81]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
0 | 1 | 1 | Allen, Miss. Elisabeth Walton | female | 29 | 0 | 0 | 24160 | 211.3375 | B5 | S | 2 | ? | St Louis, MO |
2 | 1 | 0 | Allison, Miss. Helen Loraine | female | 2 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
4 | 1 | 0 | Allison, Mrs. Hudson J C (Bessie Waldo Daniels) | female | 25 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
In [82]:
df
Out[82]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
0 | 1 | 1 | Allen, Miss. Elisabeth Walton | female | 29 | 0 | 0 | 24160 | 211.3375 | B5 | S | 2 | ? | St Louis, MO |
1 | 1 | 1 | Allison, Master. Hudson Trevor | male | 0.9167 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | 11 | ? | Montreal, PQ / Chesterville, ON |
2 | 1 | 0 | Allison, Miss. Helen Loraine | female | 2 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
3 | 1 | 0 | Allison, Mr. Hudson Joshua Creighton | male | 30 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | 135 | Montreal, PQ / Chesterville, ON |
4 | 1 | 0 | Allison, Mrs. Hudson J C (Bessie Waldo Daniels) | female | 25 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
In [85]:
df[df["survived"] == 0]
Out[85]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
2 | 1 | 0 | Allison, Miss. Helen Loraine | female | 2 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
3 | 1 | 0 | Allison, Mr. Hudson Joshua Creighton | male | 30 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | 135 | Montreal, PQ / Chesterville, ON |
4 | 1 | 0 | Allison, Mrs. Hudson J C (Bessie Waldo Daniels) | female | 25 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
In [87]:
bools = [True, False, True, True, True]df[bools]
Out[87]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
0 | 1 | 1 | Allen, Miss. Elisabeth Walton | female | 29 | 0 | 0 | 24160 | 211.3375 | B5 | S | 2 | ? | St Louis, MO |
2 | 1 | 0 | Allison, Miss. Helen Loraine | female | 2 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
3 | 1 | 0 | Allison, Mr. Hudson Joshua Creighton | male | 30 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | 135 | Montreal, PQ / Chesterville, ON |
4 | 1 | 0 | Allison, Mrs. Hudson J C (Bessie Waldo Daniels) | female | 25 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
In [90]:
titanic[titanic.survived == 1]
Out[90]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
0 | 1 | 1 | Allen, Miss. Elisabeth Walton | female | 29 | 0 | 0 | 24160 | 211.3375 | B5 | S | 2 | ? | St Louis, MO |
1 | 1 | 1 | Allison, Master. Hudson Trevor | male | 0.9167 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | 11 | ? | Montreal, PQ / Chesterville, ON |
5 | 1 | 1 | Anderson, Mr. Harry | male | 48 | 0 | 0 | 19952 | 26.55 | E12 | S | 3 | ? | New York, NY |
6 | 1 | 1 | Andrews, Miss. Kornelia Theodosia | female | 63 | 1 | 0 | 13502 | 77.9583 | D7 | S | 10 | ? | Hudson, NY |
8 | 1 | 1 | Appleton, Mrs. Edward Dale (Charlotte Lamson) | female | 53 | 2 | 0 | 11769 | 51.4792 | C101 | S | D | ? | Bayside, Queens, NY |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
1261 | 3 | 1 | Turkula, Mrs. (Hedwig) | female | 63 | 0 | 0 | 4134 | 9.5875 | ? | S | 15 | ? | ? |
1277 | 3 | 1 | Vartanian, Mr. David | male | 22 | 0 | 0 | 2658 | 7.225 | ? | C | 13 15 | ? | ? |
1286 | 3 | 1 | Whabee, Mrs. George Joseph (Shawneene Abi-Saab) | female | 38 | 0 | 0 | 2688 | 7.2292 | ? | C | C | ? | ? |
1290 | 3 | 1 | Wilkes, Mrs. James (Ellen Needs) | female | 47 | 1 | 0 | 363272 | 7 | ? | S | ? | ? | ? |
1300 | 3 | 1 | Yasbeck, Mrs. Antoni (Selini Alexander) | female | 15 | 1 | 0 | 2659 | 14.4542 | ? | C | ? | ? | ? |
500 rows × 14 columns
In [96]:
titanic[titanic.age == "18"]
Out[96]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
11 | 1 | 1 | Astor, Mrs. John Jacob (Madeleine Talmadge Force) | female | 18 | 1 | 0 | PC 17757 | 227.525 | C62 C64 | C | 4 | ? | New York, NY |
198 | 1 | 1 | Marvin, Mrs. Daniel Warner (Mary Graham Carmic... | female | 18 | 1 | 0 | 113773 | 53.1 | D30 | S | 10 | ? | New York, NY |
228 | 1 | 0 | Penasco y Castellana, Mr. Victor de Satode | male | 18 | 1 | 0 | PC 17758 | 108.9 | C65 | C | ? | ? | Madrid, Spain |
250 | 1 | 1 | Ryerson, Miss. Emily Borie | female | 18 | 2 | 2 | PC 17608 | 262.375 | B57 B59 B63 B66 | C | 4 | ? | Haverford, PA / Cooperstown, NY |
270 | 1 | 1 | Smith, Mrs. Lucien Philip (Mary Eloise Hughes) | female | 18 | 1 | 0 | 13695 | 60 | C31 | S | 6 | ? | Huntington, WV |
289 | 1 | 1 | Taussig, Miss. Ruth | female | 18 | 0 | 2 | 110413 | 79.65 | E68 | S | 8 | ? | New York, NY |
326 | 2 | 0 | Andrew, Mr. Edgardo Samuel | male | 18 | 0 | 0 | 231945 | 11.5 | ? | S | ? | ? | Buenos Aires, Argentina / New Jersey, NJ |
331 | 2 | 0 | Bailey, Mr. Percy Andrew | male | 18 | 0 | 0 | 29108 | 11.5 | ? | S | ? | ? | Penzance, Cornwall / Akron, OH |
386 | 2 | 0 | Davies, Mr. Charles Henry | male | 18 | 0 | 0 | S.O.C. 14879 | 73.5 | ? | S | ? | ? | Lyndhurst, England |
394 | 2 | 0 | Dibden, Mr. William | male | 18 | 0 | 0 | S.O.C. 14879 | 73.5 | ? | S | ? | ? | New Forest, England |
395 | 2 | 1 | Doling, Miss. Elsie | female | 18 | 0 | 1 | 231919 | 23 | ? | S | ? | ? | Southampton |
405 | 2 | 0 | Fahlstrom, Mr. Arne Jonas | male | 18 | 0 | 0 | 236171 | 13 | ? | S | ? | ? | Oslo, Norway Bayonne, NJ |
408 | 2 | 0 | Fillbrook, Mr. Joseph Charles | male | 18 | 0 | 0 | C.A. 15185 | 10.5 | ? | S | ? | ? | Cornwall / Houghton, MI |
445 | 2 | 0 | Hiltunen, Miss. Marta | female | 18 | 1 | 1 | 250650 | 13 | ? | S | ? | ? | Kontiolahti, Finland / Detroit, MI |
558 | 2 | 1 | Silven, Miss. Lyyli Karoliina | female | 18 | 0 | 2 | 250652 | 13 | ? | S | 16 | ? | Finland / Minneapolis, MN |
607 | 3 | 1 | Abrahim, Mrs. Joseph (Sophie Halaut Easu) | female | 18 | 0 | 0 | 2657 | 7.2292 | ? | C | C | ? | Greensburg, PA |
612 | 3 | 1 | Aks, Mrs. Sam (Leah Rosen) | female | 18 | 0 | 1 | 392091 | 9.35 | ? | S | 13 | ? | London, England Norfolk, VA |
619 | 3 | 0 | Allum, Mr. Owen George | male | 18 | 0 | 0 | 2223 | 8.3 | ? | S | ? | 259 | Windsor, England New York, NY |
636 | 3 | 0 | Arnold-Franchi, Mrs. Josef (Josefine Franchi) | female | 18 | 1 | 0 | 349237 | 17.8 | ? | S | ? | ? | Altdorf, Switzerland |
661 | 3 | 1 | Badman, Miss. Emily Louisa | female | 18 | 0 | 0 | A/4 31416 | 8.05 | ? | S | C | ? | London Skanteales, NY |
665 | 3 | 0 | Barbara, Miss. Saiide | female | 18 | 0 | 1 | 2691 | 14.4542 | ? | C | ? | ? | Syria Ottawa, ON |
676 | 3 | 0 | Bjorklund, Mr. Ernst Herbert | male | 18 | 0 | 0 | 347090 | 7.75 | ? | S | ? | ? | Stockholm, Sweden New York |
695 | 3 | 0 | Burns, Miss. Mary Delia | female | 18 | 0 | 0 | 330963 | 7.8792 | ? | Q | ? | ? | Co Sligo, Ireland New York, NY |
698 | 3 | 0 | Cacic, Mr. Jego Grga | male | 18 | 0 | 0 | 315091 | 8.6625 | ? | S | ? | ? | ? |
717 | 3 | 0 | Chronopoulos, Mr. Demetrios | male | 18 | 1 | 0 | 2680 | 14.4542 | ? | C | ? | ? | Greece |
719 | 3 | 1 | Cohen, Mr. Gurshon 'Gus' | male | 18 | 0 | 0 | A/5 3540 | 8.05 | ? | S | 12 | ? | London Brooklyn, NY |
786 | 3 | 0 | Edvardsson, Mr. Gustaf Hjalmar | male | 18 | 0 | 0 | 349912 | 7.775 | ? | S | ? | ? | Tofta, Sweden Joliet, IL |
799 | 3 | 0 | Fischer, Mr. Eberhard Thelander | male | 18 | 0 | 0 | 350036 | 7.7958 | ? | S | ? | ? | ? |
809 | 3 | 0 | Ford, Mr. Edward Watson | male | 18 | 2 | 2 | W./C. 6608 | 34.375 | ? | S | ? | ? | Rotherfield, Sussex, England Essex Co, MA |
859 | 3 | 0 | Hegarty, Miss. Hanora 'Nora' | female | 18 | 0 | 0 | 365226 | 6.75 | ? | Q | ? | ? | ? |
938 | 3 | 0 | Klasen, Mr. Klas Albin | male | 18 | 1 | 1 | 350404 | 7.8542 | ? | S | ? | ? | ? |
1045 | 3 | 0 | Myhrman, Mr. Pehr Fabian Oliver Malkolm | male | 18 | 0 | 0 | 347078 | 7.75 | ? | S | ? | ? | ? |
1060 | 3 | 1 | Nilsson, Miss. Berta Olivia | female | 18 | 0 | 0 | 347066 | 7.775 | ? | S | D | ? | ? |
1130 | 3 | 0 | Pettersson, Miss. Ellen Natalia | female | 18 | 0 | 0 | 347087 | 7.775 | ? | S | ? | ? | ? |
1157 | 3 | 0 | Rosblom, Mr. Viktor Richard | male | 18 | 1 | 1 | 370129 | 20.2125 | ? | S | ? | ? | ? |
1205 | 3 | 1 | Sjoblom, Miss. Anna Sofia | female | 18 | 0 | 0 | 3101265 | 7.4958 | ? | S | 16 | ? | ? |
1260 | 3 | 1 | Turja, Miss. Anna Sofia | female | 18 | 0 | 0 | 4138 | 9.8417 | ? | S | 15 | ? | ? |
1273 | 3 | 0 | Vander Planke, Miss. Augusta Maria | female | 18 | 2 | 0 | 345764 | 18 | ? | S | ? | ? | ? |
1288 | 3 | 0 | Wiklund, Mr. Jakob Alfred | male | 18 | 1 | 0 | 3101267 | 6.4958 | ? | S | ? | 314 | ? |
In [105]:
titanic[titanic.pclass != 1]
Out[105]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
323 | 2 | 0 | Abelson, Mr. Samuel | male | 30 | 1 | 0 | P/PP 3381 | 24 | ? | C | ? | ? | Russia New York, NY |
324 | 2 | 1 | Abelson, Mrs. Samuel (Hannah Wizosky) | female | 28 | 1 | 0 | P/PP 3381 | 24 | ? | C | 10 | ? | Russia New York, NY |
325 | 2 | 0 | Aldworth, Mr. Charles Augustus | male | 30 | 0 | 0 | 248744 | 13 | ? | S | ? | ? | Bryn Mawr, PA, USA |
326 | 2 | 0 | Andrew, Mr. Edgardo Samuel | male | 18 | 0 | 0 | 231945 | 11.5 | ? | S | ? | ? | Buenos Aires, Argentina / New Jersey, NJ |
327 | 2 | 0 | Andrew, Mr. Frank Thomas | male | 25 | 0 | 0 | C.A. 34050 | 10.5 | ? | S | ? | ? | Cornwall, England Houghton, MI |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
1304 | 3 | 0 | Zabour, Miss. Hileni | female | 14.5 | 1 | 0 | 2665 | 14.4542 | ? | C | ? | 328 | ? |
1305 | 3 | 0 | Zabour, Miss. Thamine | female | ? | 1 | 0 | 2665 | 14.4542 | ? | C | ? | ? | ? |
1306 | 3 | 0 | Zakarian, Mr. Mapriededer | male | 26.5 | 0 | 0 | 2656 | 7.225 | ? | C | ? | 304 | ? |
1307 | 3 | 0 | Zakarian, Mr. Ortin | male | 27 | 0 | 0 | 2670 | 7.225 | ? | C | ? | ? | ? |
1308 | 3 | 0 | Zimmerman, Mr. Leo | male | 29 | 0 | 0 | 315082 | 7.875 | ? | S | ? | ? | ? |
986 rows × 14 columns
In [108]:
houses[houses["price"] > 5000000]
Out[108]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
1164 | 1247600105 | 20141020T000000 | 5110800.0 | 5 | 5.25 | 8010 | 45517 | 2.0 | 1 | 4 | ... | 12 | 5990 | 2020 | 1999 | 0 | 98033 | 47.6767 | -122.211 | 3430 | 26788 |
1315 | 7558700030 | 20150413T000000 | 5300000.0 | 6 | 6.00 | 7390 | 24829 | 2.0 | 1 | 4 | ... | 12 | 5000 | 2390 | 1991 | 0 | 98040 | 47.5631 | -122.210 | 4320 | 24619 |
1448 | 8907500070 | 20150413T000000 | 5350000.0 | 5 | 5.00 | 8000 | 23985 | 2.0 | 0 | 4 | ... | 12 | 6720 | 1280 | 2009 | 0 | 98004 | 47.6232 | -122.220 | 4600 | 21750 |
3914 | 9808700762 | 20140611T000000 | 7062500.0 | 5 | 4.50 | 10040 | 37325 | 2.0 | 1 | 2 | ... | 11 | 7680 | 2360 | 1940 | 2001 | 98004 | 47.6500 | -122.214 | 3930 | 25449 |
4411 | 2470100110 | 20140804T000000 | 5570000.0 | 5 | 5.75 | 9200 | 35069 | 2.0 | 0 | 0 | ... | 13 | 6200 | 3000 | 2001 | 0 | 98039 | 47.6289 | -122.233 | 3560 | 24345 |
7252 | 6762700020 | 20141013T000000 | 7700000.0 | 6 | 8.00 | 12050 | 27600 | 2.5 | 0 | 3 | ... | 13 | 8570 | 3480 | 1910 | 1987 | 98102 | 47.6298 | -122.323 | 3940 | 8800 |
9254 | 9208900037 | 20140919T000000 | 6885000.0 | 6 | 7.75 | 9890 | 31374 | 2.0 | 0 | 4 | ... | 13 | 8860 | 1030 | 2001 | 0 | 98039 | 47.6305 | -122.240 | 4540 | 42730 |
7 rows × 21 columns
In [110]:
houses[houses['bedrooms'] > 10]
Out[110]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
8757 | 1773100755 | 20140821T000000 | 520000.0 | 11 | 3.00 | 3000 | 4960 | 2.0 | 0 | 0 | ... | 7 | 2400 | 600 | 1918 | 1999 | 98106 | 47.5560 | -122.363 | 1420 | 4960 |
15870 | 2402100895 | 20140625T000000 | 640000.0 | 33 | 1.75 | 1620 | 6000 | 1.0 | 0 | 0 | ... | 7 | 1040 | 580 | 1947 | 0 | 98103 | 47.6878 | -122.331 | 1330 | 4700 |
2 rows × 21 columns
In [111]:
houses[houses['bedrooms'] >= 10]
Out[111]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
8757 | 1773100755 | 20140821T000000 | 520000.0 | 11 | 3.00 | 3000 | 4960 | 2.0 | 0 | 0 | ... | 7 | 2400 | 600 | 1918 | 1999 | 98106 | 47.5560 | -122.363 | 1420 | 4960 |
13314 | 627300145 | 20140814T000000 | 1148000.0 | 10 | 5.25 | 4590 | 10920 | 1.0 | 0 | 2 | ... | 9 | 2500 | 2090 | 2008 | 0 | 98004 | 47.5861 | -122.113 | 2730 | 10400 |
15161 | 5566100170 | 20141029T000000 | 650000.0 | 10 | 2.00 | 3610 | 11914 | 2.0 | 0 | 0 | ... | 7 | 3010 | 600 | 1958 | 0 | 98006 | 47.5705 | -122.175 | 2040 | 11914 |
15870 | 2402100895 | 20140625T000000 | 640000.0 | 33 | 1.75 | 1620 | 6000 | 1.0 | 0 | 0 | ... | 7 | 1040 | 580 | 1947 | 0 | 98103 | 47.6878 | -122.331 | 1330 | 4700 |
19254 | 8812401450 | 20141229T000000 | 660000.0 | 10 | 3.00 | 2920 | 3745 | 2.0 | 0 | 0 | ... | 7 | 1860 | 1060 | 1913 | 0 | 98105 | 47.6635 | -122.320 | 1810 | 3745 |
5 rows × 21 columns
In [113]:
houses[houses["sqft_living"] < 500]
Out[113]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
465 | 8658300340 | 20140523T000000 | 80000.0 | 1 | 0.75 | 430 | 5050 | 1.0 | 0 | 0 | ... | 4 | 430 | 0 | 1912 | 0 | 98014 | 47.6499 | -121.909 | 1200 | 7500 |
860 | 1723049033 | 20140620T000000 | 245000.0 | 1 | 0.75 | 380 | 15000 | 1.0 | 0 | 0 | ... | 5 | 380 | 0 | 1963 | 0 | 98168 | 47.4810 | -122.323 | 1170 | 15000 |
1168 | 3523029041 | 20141009T000000 | 290000.0 | 2 | 0.75 | 440 | 8313 | 1.0 | 1 | 3 | ... | 5 | 440 | 0 | 1943 | 0 | 98070 | 47.4339 | -122.512 | 880 | 26289 |
4203 | 1437500015 | 20140709T000000 | 150000.0 | 3 | 0.75 | 490 | 38500 | 1.5 | 0 | 0 | ... | 5 | 490 | 0 | 1959 | 0 | 98014 | 47.7112 | -121.315 | 800 | 18297 |
4868 | 6896300380 | 20141002T000000 | 228000.0 | 0 | 1.00 | 390 | 5900 | 1.0 | 0 | 0 | ... | 4 | 390 | 0 | 1953 | 0 | 98118 | 47.5260 | -122.261 | 2170 | 6000 |
8133 | 7849202585 | 20140904T000000 | 170000.0 | 1 | 1.00 | 480 | 4560 | 1.0 | 0 | 0 | ... | 5 | 480 | 0 | 1922 | 0 | 98065 | 47.5253 | -121.826 | 890 | 4803 |
8623 | 6303400395 | 20150130T000000 | 325000.0 | 1 | 0.75 | 410 | 8636 | 1.0 | 0 | 0 | ... | 4 | 410 | 0 | 1953 | 0 | 98146 | 47.5077 | -122.357 | 1190 | 8636 |
11500 | 4322200105 | 20150331T000000 | 229050.0 | 1 | 1.00 | 420 | 3298 | 1.0 | 0 | 0 | ... | 4 | 420 | 0 | 1949 | 0 | 98136 | 47.5375 | -122.391 | 1460 | 4975 |
12075 | 8655900162 | 20150219T000000 | 156000.0 | 1 | 0.75 | 470 | 15000 | 1.0 | 0 | 0 | ... | 4 | 470 | 0 | 1947 | 0 | 98014 | 47.6554 | -121.908 | 1730 | 22500 |
14466 | 7549801385 | 20140612T000000 | 280000.0 | 1 | 0.75 | 420 | 6720 | 1.0 | 0 | 0 | ... | 5 | 420 | 0 | 1922 | 0 | 98108 | 47.5520 | -122.311 | 1420 | 6720 |
15248 | 1320069249 | 20141020T000000 | 192500.0 | 1 | 1.00 | 470 | 63737 | 1.0 | 0 | 2 | ... | 5 | 470 | 0 | 1924 | 0 | 98022 | 47.2163 | -121.984 | 1350 | 46762 |
15381 | 2856101479 | 20140701T000000 | 276000.0 | 1 | 0.75 | 370 | 1801 | 1.0 | 0 | 0 | ... | 5 | 370 | 0 | 1923 | 0 | 98117 | 47.6778 | -122.389 | 1340 | 5000 |
17394 | 745000005 | 20140825T000000 | 145000.0 | 1 | 0.75 | 480 | 9750 | 1.0 | 0 | 0 | ... | 4 | 480 | 0 | 1948 | 0 | 98146 | 47.4982 | -122.362 | 1550 | 9924 |
18052 | 1352300580 | 20141114T000000 | 247000.0 | 1 | 1.00 | 460 | 4120 | 1.0 | 0 | 0 | ... | 4 | 460 | 0 | 1937 | 0 | 98055 | 47.4868 | -122.199 | 990 | 4120 |
18379 | 1222029077 | 20141029T000000 | 265000.0 | 0 | 0.75 | 384 | 213444 | 1.0 | 0 | 0 | ... | 4 | 384 | 0 | 2003 | 0 | 98070 | 47.4177 | -122.491 | 1920 | 224341 |
19452 | 3980300371 | 20140926T000000 | 142000.0 | 0 | 0.00 | 290 | 20875 | 1.0 | 0 | 0 | ... | 1 | 290 | 0 | 1963 | 0 | 98024 | 47.5308 | -121.888 | 1620 | 22850 |
21332 | 9266700190 | 20150511T000000 | 245000.0 | 1 | 1.00 | 390 | 2000 | 1.0 | 0 | 0 | ... | 6 | 390 | 0 | 1920 | 0 | 98103 | 47.6938 | -122.347 | 1340 | 5100 |
17 rows × 21 columns
In [114]:
houses[houses["sqft_living"] <= 500]
Out[114]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
465 | 8658300340 | 20140523T000000 | 80000.0 | 1 | 0.75 | 430 | 5050 | 1.0 | 0 | 0 | ... | 4 | 430 | 0 | 1912 | 0 | 98014 | 47.6499 | -121.909 | 1200 | 7500 |
860 | 1723049033 | 20140620T000000 | 245000.0 | 1 | 0.75 | 380 | 15000 | 1.0 | 0 | 0 | ... | 5 | 380 | 0 | 1963 | 0 | 98168 | 47.4810 | -122.323 | 1170 | 15000 |
1168 | 3523029041 | 20141009T000000 | 290000.0 | 2 | 0.75 | 440 | 8313 | 1.0 | 1 | 3 | ... | 5 | 440 | 0 | 1943 | 0 | 98070 | 47.4339 | -122.512 | 880 | 26289 |
4203 | 1437500015 | 20140709T000000 | 150000.0 | 3 | 0.75 | 490 | 38500 | 1.5 | 0 | 0 | ... | 5 | 490 | 0 | 1959 | 0 | 98014 | 47.7112 | -121.315 | 800 | 18297 |
4651 | 859000110 | 20141002T000000 | 125000.0 | 1 | 1.00 | 500 | 7440 | 1.0 | 0 | 0 | ... | 5 | 500 | 0 | 1928 | 0 | 98106 | 47.5252 | -122.362 | 1350 | 7440 |
4868 | 6896300380 | 20141002T000000 | 228000.0 | 0 | 1.00 | 390 | 5900 | 1.0 | 0 | 0 | ... | 4 | 390 | 0 | 1953 | 0 | 98118 | 47.5260 | -122.261 | 2170 | 6000 |
8133 | 7849202585 | 20140904T000000 | 170000.0 | 1 | 1.00 | 480 | 4560 | 1.0 | 0 | 0 | ... | 5 | 480 | 0 | 1922 | 0 | 98065 | 47.5253 | -121.826 | 890 | 4803 |
8623 | 6303400395 | 20150130T000000 | 325000.0 | 1 | 0.75 | 410 | 8636 | 1.0 | 0 | 0 | ... | 4 | 410 | 0 | 1953 | 0 | 98146 | 47.5077 | -122.357 | 1190 | 8636 |
11500 | 4322200105 | 20150331T000000 | 229050.0 | 1 | 1.00 | 420 | 3298 | 1.0 | 0 | 0 | ... | 4 | 420 | 0 | 1949 | 0 | 98136 | 47.5375 | -122.391 | 1460 | 4975 |
12075 | 8655900162 | 20150219T000000 | 156000.0 | 1 | 0.75 | 470 | 15000 | 1.0 | 0 | 0 | ... | 4 | 470 | 0 | 1947 | 0 | 98014 | 47.6554 | -121.908 | 1730 | 22500 |
14466 | 7549801385 | 20140612T000000 | 280000.0 | 1 | 0.75 | 420 | 6720 | 1.0 | 0 | 0 | ... | 5 | 420 | 0 | 1922 | 0 | 98108 | 47.5520 | -122.311 | 1420 | 6720 |
15248 | 1320069249 | 20141020T000000 | 192500.0 | 1 | 1.00 | 470 | 63737 | 1.0 | 0 | 2 | ... | 5 | 470 | 0 | 1924 | 0 | 98022 | 47.2163 | -121.984 | 1350 | 46762 |
15381 | 2856101479 | 20140701T000000 | 276000.0 | 1 | 0.75 | 370 | 1801 | 1.0 | 0 | 0 | ... | 5 | 370 | 0 | 1923 | 0 | 98117 | 47.6778 | -122.389 | 1340 | 5000 |
17394 | 745000005 | 20140825T000000 | 145000.0 | 1 | 0.75 | 480 | 9750 | 1.0 | 0 | 0 | ... | 4 | 480 | 0 | 1948 | 0 | 98146 | 47.4982 | -122.362 | 1550 | 9924 |
18052 | 1352300580 | 20141114T000000 | 247000.0 | 1 | 1.00 | 460 | 4120 | 1.0 | 0 | 0 | ... | 4 | 460 | 0 | 1937 | 0 | 98055 | 47.4868 | -122.199 | 990 | 4120 |
18379 | 1222029077 | 20141029T000000 | 265000.0 | 0 | 0.75 | 384 | 213444 | 1.0 | 0 | 0 | ... | 4 | 384 | 0 | 2003 | 0 | 98070 | 47.4177 | -122.491 | 1920 | 224341 |
19452 | 3980300371 | 20140926T000000 | 142000.0 | 0 | 0.00 | 290 | 20875 | 1.0 | 0 | 0 | ... | 1 | 290 | 0 | 1963 | 0 | 98024 | 47.5308 | -121.888 | 1620 | 22850 |
21332 | 9266700190 | 20150511T000000 | 245000.0 | 1 | 1.00 | 390 | 2000 | 1.0 | 0 | 0 | ... | 6 | 390 | 0 | 1920 | 0 | 98103 | 47.6938 | -122.347 | 1340 | 5100 |
18 rows × 21 columns
In [133]:
houses[houses["bedrooms"].between(5, 7)]
Out[133]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
14 | 1175000570 | 20150312T000000 | 530000.0 | 5 | 2.00 | 1810 | 4850 | 1.5 | 0 | 0 | ... | 7 | 1810 | 0 | 1900 | 0 | 98107 | 47.6700 | -122.394 | 1360 | 4850 |
22 | 7137970340 | 20140703T000000 | 285000.0 | 5 | 2.50 | 2270 | 6300 | 2.0 | 0 | 0 | ... | 8 | 2270 | 0 | 1995 | 0 | 98092 | 47.3266 | -122.169 | 2240 | 7005 |
42 | 7203220400 | 20140707T000000 | 861990.0 | 5 | 2.75 | 3595 | 5639 | 2.0 | 0 | 0 | ... | 9 | 3595 | 0 | 2014 | 0 | 98053 | 47.6848 | -122.016 | 3625 | 5639 |
51 | 7231300125 | 20150217T000000 | 345000.0 | 5 | 2.50 | 3150 | 9134 | 1.0 | 0 | 0 | ... | 8 | 1640 | 1510 | 1966 | 0 | 98056 | 47.4934 | -122.189 | 1990 | 9133 |
54 | 4217401195 | 20150303T000000 | 920000.0 | 5 | 2.25 | 2730 | 6000 | 1.5 | 0 | 0 | ... | 8 | 2130 | 600 | 1927 | 0 | 98105 | 47.6571 | -122.281 | 2730 | 6000 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
21564 | 7168100015 | 20141009T000000 | 579950.0 | 5 | 2.75 | 3080 | 5752 | 2.0 | 0 | 0 | ... | 9 | 3080 | 0 | 2014 | 0 | 98059 | 47.4922 | -122.153 | 3000 | 4650 |
21576 | 9253900271 | 20150107T000000 | 3567000.0 | 5 | 4.50 | 4850 | 10584 | 2.0 | 1 | 4 | ... | 10 | 3540 | 1310 | 2007 | 0 | 98008 | 47.5943 | -122.110 | 3470 | 18270 |
21593 | 8672200110 | 20150317T000000 | 1088000.0 | 5 | 3.75 | 4170 | 8142 | 2.0 | 0 | 2 | ... | 10 | 4170 | 0 | 2006 | 0 | 98056 | 47.5354 | -122.181 | 3030 | 7980 |
21596 | 7502800100 | 20140813T000000 | 679950.0 | 5 | 2.75 | 3600 | 9437 | 2.0 | 0 | 0 | ... | 9 | 3600 | 0 | 2014 | 0 | 98059 | 47.4822 | -122.131 | 3550 | 9421 |
21600 | 249000205 | 20141015T000000 | 1537000.0 | 5 | 3.75 | 4470 | 8088 | 2.0 | 0 | 0 | ... | 11 | 4470 | 0 | 2008 | 0 | 98004 | 47.6321 | -122.200 | 2780 | 8964 |
1911 rows × 21 columns
In [134]:
houses[houses["grade"].between(11,13)]
Out[134]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
5 | 7237550310 | 20140512T000000 | 1225000.0 | 4 | 4.50 | 5420 | 101930 | 1.0 | 0 | 0 | ... | 11 | 3890 | 1530 | 2001 | 0 | 98053 | 47.6561 | -122.005 | 4760 | 101930 |
70 | 1525059190 | 20140912T000000 | 1040000.0 | 5 | 3.25 | 4770 | 50094 | 1.0 | 0 | 0 | ... | 11 | 3070 | 1700 | 1973 | 0 | 98005 | 47.6525 | -122.160 | 3530 | 38917 |
153 | 7855801670 | 20150401T000000 | 2250000.0 | 4 | 3.25 | 5180 | 19850 | 2.0 | 0 | 3 | ... | 12 | 3540 | 1640 | 2006 | 0 | 98006 | 47.5620 | -122.162 | 3160 | 9750 |
269 | 7960900060 | 20150504T000000 | 2900000.0 | 4 | 3.25 | 5050 | 20100 | 1.5 | 0 | 2 | ... | 11 | 4750 | 300 | 1982 | 2008 | 98004 | 47.6312 | -122.223 | 3890 | 20060 |
270 | 4054500390 | 20141007T000000 | 1365000.0 | 4 | 4.75 | 5310 | 57346 | 2.0 | 0 | 0 | ... | 11 | 5310 | 0 | 1989 | 0 | 98077 | 47.7285 | -122.042 | 4180 | 47443 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
21532 | 324069112 | 20140617T000000 | 1325000.0 | 4 | 4.00 | 4420 | 16526 | 2.0 | 0 | 0 | ... | 11 | 4420 | 0 | 2013 | 0 | 98075 | 47.5914 | -122.027 | 3510 | 50447 |
21548 | 8835770330 | 20140819T000000 | 1057000.0 | 2 | 1.50 | 2370 | 184231 | 2.0 | 0 | 0 | ... | 11 | 2370 | 0 | 2005 | 0 | 98045 | 47.4543 | -121.778 | 3860 | 151081 |
21551 | 1561750040 | 20141224T000000 | 1375000.0 | 5 | 4.50 | 4350 | 13405 | 2.0 | 0 | 0 | ... | 11 | 4350 | 0 | 2014 | 0 | 98074 | 47.6018 | -122.060 | 3990 | 7208 |
21590 | 7430200100 | 20140514T000000 | 1222500.0 | 4 | 3.50 | 4910 | 9444 | 1.5 | 0 | 0 | ... | 11 | 3110 | 1800 | 2007 | 0 | 98074 | 47.6502 | -122.066 | 4560 | 11063 |
21600 | 249000205 | 20141015T000000 | 1537000.0 | 5 | 3.75 | 4470 | 8088 | 2.0 | 0 | 0 | ... | 11 | 4470 | 0 | 2008 | 0 | 98004 | 47.6321 | -122.200 | 2780 | 8964 |
502 rows × 21 columns
In [142]:
countries = ["India", "Japan", "South Korea"]netflix[netflix["country"].isin(countries)]
Out[142]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
4 | s5 | TV Show | Kota Factory | NaN | Mayur More, Jitendra Kumar, Ranjan Raj, Alam K... | India | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, Romantic TV Shows, TV ... | In a city of coaching centers known to train I... |
24 | s25 | Movie | Jeans | S. Shankar | Prashanth, Aishwarya Rai Bachchan, Sri Lakshmi... | India | September 21, 2021 | 1998 | TV-14 | 166 min | Comedies, International Movies, Romantic Movies | When the father of the man she loves insists t... |
39 | s40 | TV Show | Chhota Bheem | NaN | Vatsal Dubey, Julie Tejwani, Rupa Bhimani, Jig... | India | September 16, 2021 | 2021 | TV-Y7 | 3 Seasons | Kids' TV | A brave, energetic little boy with superhuman ... |
50 | s51 | TV Show | Dharmakshetra | NaN | Kashmira Irani, Chandan Anand, Dinesh Mehta, A... | India | September 15, 2021 | 2014 | TV-PG | 1 Season | International TV Shows, TV Dramas, TV Sci-Fi &... | After the ancient Great War, the god Chitragup... |
51 | s52 | Movie | InuYasha the Movie 2: The Castle Beyond the Lo... | Toshiya Shinohara | Kappei Yamaguchi, Satsuki Yukino, Mieko Harada... | Japan | September 15, 2021 | 2002 | TV-14 | 99 min | Action & Adventure, Anime Features, Internatio... | With their biggest foe seemingly defeated, Inu... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
8773 | s8774 | Movie | Yanda Kartavya Aahe | Kedar Shinde | Ankush Choudhary, Smita Shewale, Mohan Joshi, ... | India | January 1, 2018 | 2006 | TV-PG | 151 min | Comedies, Dramas, International Movies | Thanks to an arranged marriage that was design... |
8775 | s8776 | TV Show | Yeh Meri Family | NaN | Vishesh Bansal, Mona Singh, Akarsh Khurana, Ah... | India | August 31, 2018 | 2018 | TV-PG | 1 Season | International TV Shows, TV Comedies | In the summer of 1998, middle child Harshu bal... |
8798 | s8799 | Movie | Zed Plus | Chandra Prakash Dwivedi | Adil Hussain, Mona Singh, K.K. Raina, Sanjay M... | India | December 31, 2019 | 2014 | TV-MA | 131 min | Comedies, Dramas, International Movies | A philandering small-town mechanic's political... |
8799 | s8800 | Movie | Zenda | Avadhoot Gupte | Santosh Juvekar, Siddharth Chandekar, Sachit P... | India | February 15, 2018 | 2009 | TV-14 | 120 min | Dramas, International Movies | A change in the leadership of a political part... |
8806 | s8807 | Movie | Zubaan | Mozez Singh | Vicky Kaushal, Sarah-Jane Dias, Raaghav Chanan... | India | March 2, 2019 | 2015 | TV-14 | 111 min | Dramas, International Movies, Music & Musicals | A scrappy but poor boy worms his way into a ty... |
1416 rows × 12 columns
In [146]:
mature = netflix["rating"].isin(["TV-MA", "R", "PG-13"])netflix[mature]
Out[146]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
0 | s1 | Movie | Dick Johnson Is Dead | Kirsten Johnson | NaN | United States | September 25, 2021 | 2020 | PG-13 | 90 min | Documentaries | As her father nears the end of his life, filmm... |
1 | s2 | TV Show | Blood & Water | NaN | Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban... | South Africa | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, TV Dramas, TV Mysteries | After crossing paths at a party, a Cape Town t... |
2 | s3 | TV Show | Ganglands | Julien Leclercq | Sami Bouajila, Tracy Gotoas, Samuel Jouy, Nabi... | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Crime TV Shows, International TV Shows, TV Act... | To protect his family from a powerful drug lor... |
3 | s4 | TV Show | Jailbirds New Orleans | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Docuseries, Reality TV | Feuds, flirtations and toilet talk go down amo... |
4 | s5 | TV Show | Kota Factory | NaN | Mayur More, Jitendra Kumar, Ranjan Raj, Alam K... | India | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, Romantic TV Shows, TV ... | In a city of coaching centers known to train I... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
8791 | s8792 | Movie | Young Adult | Jason Reitman | Charlize Theron, Patton Oswalt, Patrick Wilson... | United States | November 20, 2019 | 2011 | R | 94 min | Comedies, Dramas, Independent Movies | When a divorced writer gets a letter from an o... |
8798 | s8799 | Movie | Zed Plus | Chandra Prakash Dwivedi | Adil Hussain, Mona Singh, K.K. Raina, Sanjay M... | India | December 31, 2019 | 2014 | TV-MA | 131 min | Comedies, Dramas, International Movies | A philandering small-town mechanic's political... |
8801 | s8802 | Movie | Zinzana | Majid Al Ansari | Ali Suliman, Saleh Bakri, Yasa, Ali Al-Jabri, ... | United Arab Emirates, Jordan | March 9, 2016 | 2015 | TV-MA | 96 min | Dramas, International Movies, Thrillers | Recovering alcoholic Talal wakes up inside a s... |
8802 | s8803 | Movie | Zodiac | David Fincher | Mark Ruffalo, Jake Gyllenhaal, Robert Downey J... | United States | November 20, 2019 | 2007 | R | 158 min | Cult Movies, Dramas, Thrillers | A political cartoonist, a crime reporter and a... |
8804 | s8805 | Movie | Zombieland | Ruben Fleischer | Jesse Eisenberg, Woody Harrelson, Emma Stone, ... | United States | November 1, 2019 | 2009 | R | 88 min | Comedies, Horror Movies | Looking to survive in a world taken over by zo... |
4496 rows × 12 columns
In [155]:
women = titanic.sex == 'female'died = titanic.survived == 0titanic[women & died]
Out[155]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
2 | 1 | 0 | Allison, Miss. Helen Loraine | female | 2 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
4 | 1 | 0 | Allison, Mrs. Hudson J C (Bessie Waldo Daniels) | female | 25 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | ? | Montreal, PQ / Chesterville, ON |
105 | 1 | 0 | Evans, Miss. Edith Corse | female | 36 | 0 | 0 | PC 17531 | 31.6792 | A29 | C | ? | ? | New York, NY |
169 | 1 | 0 | Isham, Miss. Ann Elizabeth | female | 50 | 0 | 0 | PC 17595 | 28.7125 | C49 | C | ? | ? | Paris, France New York, NY |
286 | 1 | 0 | Straus, Mrs. Isidor (Rosalie Ida Blun) | female | 63 | 1 | 0 | PC 17483 | 221.7792 | C55 C57 | S | ? | ? | New York, NY |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
1273 | 3 | 0 | Vander Planke, Miss. Augusta Maria | female | 18 | 2 | 0 | 345764 | 18 | ? | S | ? | ? | ? |
1276 | 3 | 0 | Vander Planke, Mrs. Julius (Emelia Maria Vande... | female | 31 | 1 | 0 | 345763 | 18 | ? | S | ? | ? | ? |
1279 | 3 | 0 | Vestrom, Miss. Hulda Amanda Adolfina | female | 14 | 0 | 0 | 350406 | 7.8542 | ? | S | ? | ? | ? |
1304 | 3 | 0 | Zabour, Miss. Hileni | female | 14.5 | 1 | 0 | 2665 | 14.4542 | ? | C | ? | 328 | ? |
1305 | 3 | 0 | Zabour, Miss. Thamine | female | ? | 1 | 0 | 2665 | 14.4542 | ? | C | ? | ? | ? |
127 rows × 14 columns
In [160]:
houses[(houses["waterfront"] == 1) & (houses["price"] < 500000)]
Out[160]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
264 | 2123039032 | 20141027T000000 | 369900.0 | 1 | 0.75 | 760 | 10079 | 1.0 | 1 | 4 | ... | 5 | 760 | 0 | 1936 | 0 | 98070 | 47.4683 | -122.438 | 1230 | 14267 |
1168 | 3523029041 | 20141009T000000 | 290000.0 | 2 | 0.75 | 440 | 8313 | 1.0 | 1 | 3 | ... | 5 | 440 | 0 | 1943 | 0 | 98070 | 47.4339 | -122.512 | 880 | 26289 |
1949 | 1922039062 | 20150420T000000 | 480000.0 | 2 | 1.50 | 1008 | 26487 | 1.0 | 1 | 4 | ... | 6 | 1008 | 0 | 1943 | 2002 | 98070 | 47.3853 | -122.479 | 1132 | 24079 |
3829 | 8550001515 | 20141001T000000 | 429592.0 | 2 | 2.75 | 1992 | 10946 | 1.5 | 1 | 4 | ... | 6 | 1288 | 704 | 1903 | 0 | 98070 | 47.3551 | -122.475 | 1110 | 8328 |
6102 | 222029026 | 20140917T000000 | 340000.0 | 2 | 0.75 | 1060 | 48292 | 1.0 | 1 | 2 | ... | 6 | 560 | 500 | 1947 | 0 | 98070 | 47.4285 | -122.511 | 750 | 80201 |
8277 | 221029019 | 20150428T000000 | 400000.0 | 3 | 2.50 | 2090 | 32718 | 2.0 | 1 | 4 | ... | 7 | 1550 | 540 | 1919 | 1983 | 98070 | 47.3338 | -122.511 | 1200 | 192268 |
8450 | 121039042 | 20150313T000000 | 425000.0 | 3 | 2.75 | 3610 | 107386 | 1.5 | 1 | 3 | ... | 8 | 3130 | 480 | 1918 | 1962 | 98023 | 47.3351 | -122.362 | 2630 | 42126 |
11556 | 2013802030 | 20140911T000000 | 357000.0 | 3 | 2.00 | 2460 | 53882 | 1.0 | 1 | 4 | ... | 7 | 2460 | 0 | 1955 | 0 | 98198 | 47.3811 | -122.325 | 2660 | 32625 |
14827 | 2423029009 | 20140617T000000 | 465000.0 | 2 | 2.00 | 1494 | 19271 | 2.0 | 1 | 4 | ... | 7 | 1494 | 0 | 1943 | 1997 | 98070 | 47.4728 | -122.497 | 1494 | 43583 |
16570 | 2923039243 | 20141113T000000 | 340000.0 | 4 | 1.00 | 1200 | 11834 | 1.0 | 1 | 3 | ... | 6 | 1200 | 0 | 1972 | 0 | 98070 | 47.4557 | -122.443 | 1670 | 47462 |
18275 | 2781600195 | 20141117T000000 | 285000.0 | 1 | 1.00 | 1060 | 54846 | 1.0 | 1 | 4 | ... | 5 | 1060 | 0 | 1935 | 0 | 98070 | 47.4716 | -122.445 | 2258 | 31762 |
18848 | 7631800110 | 20140918T000000 | 380000.0 | 3 | 2.50 | 1980 | 17342 | 2.0 | 1 | 4 | ... | 10 | 1580 | 400 | 1984 | 0 | 98166 | 47.4551 | -122.373 | 2060 | 17313 |
19002 | 5216200090 | 20140616T000000 | 385000.0 | 2 | 1.00 | 830 | 26329 | 1.0 | 1 | 3 | ... | 6 | 830 | 0 | 1928 | 0 | 98070 | 47.4012 | -122.425 | 2030 | 27338 |
13 rows × 21 columns
In [169]:
houses[houses["view"]== 4]houses[houses["grade"] >= 11]houses[(houses["grade"] >= 11) & (houses["view"] == 4)]
Out[169]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
540 | 622049114 | 20150218T000000 | 2125000.0 | 3 | 2.50 | 5403 | 24069 | 2.0 | 1 | 4 | ... | 12 | 5403 | 0 | 1976 | 0 | 98166 | 47.4169 | -122.348 | 3980 | 104374 |
1164 | 1247600105 | 20141020T000000 | 5110800.0 | 5 | 5.25 | 8010 | 45517 | 2.0 | 1 | 4 | ... | 12 | 5990 | 2020 | 1999 | 0 | 98033 | 47.6767 | -122.211 | 3430 | 26788 |
1315 | 7558700030 | 20150413T000000 | 5300000.0 | 6 | 6.00 | 7390 | 24829 | 2.0 | 1 | 4 | ... | 12 | 5000 | 2390 | 1991 | 0 | 98040 | 47.5631 | -122.210 | 4320 | 24619 |
1448 | 8907500070 | 20150413T000000 | 5350000.0 | 5 | 5.00 | 8000 | 23985 | 2.0 | 0 | 4 | ... | 12 | 6720 | 1280 | 2009 | 0 | 98004 | 47.6232 | -122.220 | 4600 | 21750 |
2085 | 8106100105 | 20141114T000000 | 3850000.0 | 4 | 4.25 | 5770 | 21300 | 2.0 | 1 | 4 | ... | 11 | 5770 | 0 | 1980 | 0 | 98040 | 47.5850 | -122.222 | 4620 | 22748 |
2444 | 7524900003 | 20141210T000000 | 3278000.0 | 2 | 1.75 | 6840 | 10000 | 2.5 | 1 | 4 | ... | 11 | 4350 | 2490 | 2001 | 0 | 98008 | 47.6042 | -122.112 | 3120 | 12300 |
2626 | 7738500731 | 20140815T000000 | 4500000.0 | 5 | 5.50 | 6640 | 40014 | 2.0 | 1 | 4 | ... | 12 | 6350 | 290 | 2004 | 0 | 98155 | 47.7493 | -122.280 | 3030 | 23408 |
2713 | 7851980260 | 20140730T000000 | 1110000.0 | 5 | 3.50 | 7350 | 12231 | 2.0 | 0 | 4 | ... | 11 | 4750 | 2600 | 2001 | 0 | 98065 | 47.5373 | -121.865 | 5380 | 12587 |
3157 | 1827200265 | 20140911T000000 | 1899000.0 | 2 | 2.75 | 3690 | 32044 | 2.0 | 1 | 4 | ... | 12 | 3690 | 0 | 1989 | 0 | 98166 | 47.4485 | -122.369 | 2310 | 26988 |
3586 | 9272200090 | 20150204T000000 | 1598890.0 | 4 | 4.50 | 3780 | 6000 | 2.0 | 0 | 4 | ... | 11 | 2770 | 1010 | 1910 | 1977 | 98116 | 47.5922 | -122.388 | 2660 | 6000 |
4013 | 724069059 | 20140509T000000 | 2400000.0 | 3 | 2.25 | 3000 | 11665 | 1.5 | 1 | 4 | ... | 11 | 3000 | 0 | 2001 | 0 | 98075 | 47.5884 | -122.086 | 3000 | 15959 |
4190 | 2303900090 | 20140729T000000 | 2880500.0 | 4 | 2.50 | 5760 | 32033 | 2.0 | 0 | 4 | ... | 12 | 4390 | 1370 | 1994 | 0 | 98177 | 47.7288 | -122.370 | 3420 | 28475 |
4406 | 3505100756 | 20141106T000000 | 2050000.0 | 4 | 3.00 | 4280 | 18834 | 1.0 | 0 | 4 | ... | 11 | 2180 | 2100 | 1971 | 0 | 98116 | 47.5811 | -122.400 | 2490 | 8858 |
5749 | 6744701310 | 20150415T000000 | 1850000.0 | 4 | 2.50 | 3830 | 11972 | 1.0 | 1 | 4 | ... | 11 | 2370 | 1460 | 1981 | 0 | 98155 | 47.7404 | -122.284 | 3080 | 12297 |
5850 | 3585900500 | 20150402T000000 | 1525000.0 | 4 | 4.25 | 4720 | 21000 | 3.0 | 0 | 4 | ... | 11 | 4720 | 0 | 1971 | 0 | 98177 | 47.7591 | -122.376 | 3010 | 20000 |
6233 | 2024069008 | 20140619T000000 | 2200000.0 | 5 | 4.75 | 5990 | 10450 | 2.0 | 1 | 4 | ... | 11 | 4050 | 1940 | 2002 | 0 | 98027 | 47.5554 | -122.077 | 3330 | 14810 |
6501 | 2626069030 | 20150209T000000 | 1940000.0 | 4 | 5.75 | 7220 | 223462 | 2.0 | 0 | 4 | ... | 12 | 6220 | 1000 | 2000 | 0 | 98053 | 47.7097 | -122.013 | 2680 | 7593 |
6508 | 4217402115 | 20150421T000000 | 3650000.0 | 6 | 4.75 | 5480 | 19401 | 1.5 | 1 | 4 | ... | 11 | 3910 | 1570 | 1936 | 0 | 98105 | 47.6515 | -122.277 | 3510 | 15810 |
7269 | 4139470010 | 20141006T000000 | 1615000.0 | 4 | 3.25 | 4250 | 12281 | 2.0 | 0 | 4 | ... | 12 | 3020 | 1230 | 1996 | 0 | 98006 | 47.5507 | -122.113 | 4940 | 12941 |
7313 | 4131900066 | 20140825T000000 | 3100000.0 | 3 | 3.00 | 3920 | 13085 | 2.0 | 1 | 4 | ... | 11 | 3920 | 0 | 1996 | 0 | 98040 | 47.5716 | -122.204 | 3450 | 13287 |
7700 | 3761700053 | 20150105T000000 | 2150000.0 | 3 | 2.75 | 3470 | 9610 | 3.0 | 1 | 4 | ... | 11 | 3470 | 0 | 1989 | 2000 | 98034 | 47.7205 | -122.260 | 4130 | 11875 |
8092 | 1924059029 | 20140617T000000 | 4668000.0 | 5 | 6.75 | 9640 | 13068 | 1.0 | 1 | 4 | ... | 12 | 4820 | 4820 | 1983 | 2009 | 98040 | 47.5570 | -122.210 | 3270 | 10454 |
8174 | 9279700150 | 20150212T000000 | 1625000.0 | 4 | 3.75 | 4410 | 8112 | 3.0 | 0 | 4 | ... | 11 | 3570 | 840 | 2003 | 0 | 98116 | 47.5888 | -122.392 | 2770 | 5750 |
8568 | 8653600100 | 20150330T000000 | 750000.0 | 5 | 2.50 | 3120 | 15593 | 2.0 | 0 | 4 | ... | 11 | 3120 | 0 | 1986 | 0 | 98074 | 47.6142 | -122.065 | 3390 | 17003 |
9254 | 9208900037 | 20140919T000000 | 6885000.0 | 6 | 7.75 | 9890 | 31374 | 2.0 | 0 | 4 | ... | 13 | 8860 | 1030 | 2001 | 0 | 98039 | 47.6305 | -122.240 | 4540 | 42730 |
10385 | 3225069301 | 20140612T000000 | 1228000.0 | 4 | 2.50 | 5730 | 44947 | 2.0 | 0 | 4 | ... | 11 | 4280 | 1450 | 1991 | 0 | 98074 | 47.6052 | -122.064 | 3310 | 17628 |
10465 | 333100295 | 20141124T000000 | 3120000.0 | 3 | 3.50 | 4490 | 56609 | 2.0 | 1 | 4 | ... | 12 | 4490 | 0 | 1993 | 0 | 98034 | 47.6997 | -122.240 | 2710 | 51330 |
10665 | 7852160310 | 20140814T000000 | 1010000.0 | 4 | 2.75 | 3430 | 15877 | 1.0 | 0 | 4 | ... | 11 | 3430 | 0 | 2005 | 0 | 98065 | 47.5364 | -121.856 | 4080 | 14577 |
11402 | 3426049284 | 20140819T000000 | 2300000.0 | 4 | 3.25 | 4110 | 15929 | 2.0 | 1 | 4 | ... | 12 | 2720 | 1390 | 2001 | 0 | 98115 | 47.6934 | -122.271 | 2640 | 15929 |
11535 | 8964800890 | 20150109T000000 | 3200000.0 | 3 | 3.25 | 4560 | 13363 | 1.0 | 0 | 4 | ... | 11 | 2760 | 1800 | 1995 | 0 | 98004 | 47.6205 | -122.214 | 4060 | 13362 |
11729 | 2303900045 | 20140623T000000 | 1580000.0 | 4 | 2.50 | 4570 | 74487 | 2.0 | 0 | 4 | ... | 12 | 4570 | 0 | 1948 | 1985 | 98177 | 47.7282 | -122.372 | 3810 | 74487 |
11829 | 4139420640 | 20141030T000000 | 1785000.0 | 4 | 3.50 | 5490 | 14300 | 1.0 | 0 | 4 | ... | 12 | 2910 | 2580 | 1996 | 0 | 98006 | 47.5511 | -122.114 | 4290 | 13822 |
12429 | 98001070 | 20140818T000000 | 1169000.0 | 5 | 4.25 | 4610 | 13252 | 2.0 | 0 | 4 | ... | 11 | 4610 | 0 | 2004 | 0 | 98075 | 47.5878 | -121.969 | 4400 | 15154 |
12777 | 1225069038 | 20140505T000000 | 2280000.0 | 7 | 8.00 | 13540 | 307752 | 3.0 | 0 | 4 | ... | 12 | 9410 | 4130 | 1999 | 0 | 98053 | 47.6675 | -121.986 | 4850 | 217800 |
12872 | 2424049029 | 20140529T000000 | 3100000.0 | 6 | 4.25 | 6980 | 15682 | 3.0 | 0 | 4 | ... | 12 | 5330 | 1650 | 1999 | 0 | 98040 | 47.5552 | -122.231 | 3930 | 18367 |
13068 | 7856410411 | 20140922T000000 | 1698890.0 | 4 | 4.50 | 3860 | 15246 | 2.0 | 0 | 4 | ... | 11 | 2940 | 920 | 2004 | 0 | 98006 | 47.5600 | -122.161 | 3750 | 14790 |
13528 | 3025059124 | 20140828T000000 | 3168750.0 | 5 | 3.50 | 4330 | 11979 | 1.0 | 0 | 4 | ... | 12 | 2090 | 2240 | 2008 | 0 | 98004 | 47.6251 | -122.218 | 4320 | 12000 |
13710 | 2923500230 | 20141216T000000 | 2600000.0 | 4 | 4.50 | 5270 | 12195 | 2.0 | 1 | 4 | ... | 11 | 3400 | 1870 | 1979 | 0 | 98027 | 47.5696 | -122.090 | 3390 | 9905 |
13770 | 1795800040 | 20140903T000000 | 1350000.0 | 4 | 3.25 | 5370 | 20388 | 2.0 | 0 | 4 | ... | 11 | 5370 | 0 | 1990 | 0 | 98198 | 47.4050 | -122.331 | 2770 | 22270 |
14083 | 3625059043 | 20140904T000000 | 3300000.0 | 5 | 4.75 | 6200 | 13873 | 2.0 | 1 | 4 | ... | 11 | 4440 | 1760 | 1989 | 0 | 98008 | 47.6050 | -122.112 | 2940 | 13525 |
14556 | 2303900035 | 20140611T000000 | 2888000.0 | 5 | 6.25 | 8670 | 64033 | 2.0 | 0 | 4 | ... | 13 | 6120 | 2550 | 1965 | 2003 | 98177 | 47.7295 | -122.372 | 4140 | 81021 |
14774 | 9412400220 | 20140710T000000 | 1612500.0 | 4 | 2.75 | 5470 | 18200 | 2.0 | 1 | 4 | ... | 11 | 3730 | 1740 | 1992 | 0 | 98118 | 47.5316 | -122.263 | 3620 | 15100 |
15255 | 2425049063 | 20140911T000000 | 3640900.0 | 4 | 3.25 | 4830 | 22257 | 2.0 | 1 | 4 | ... | 11 | 4830 | 0 | 1990 | 0 | 98039 | 47.6409 | -122.241 | 3820 | 25582 |
15258 | 1732800780 | 20150212T000000 | 3065000.0 | 5 | 3.00 | 4150 | 7500 | 2.5 | 0 | 4 | ... | 11 | 3510 | 640 | 1909 | 0 | 98119 | 47.6303 | -122.362 | 2250 | 4050 |
15482 | 624069108 | 20140812T000000 | 3200000.0 | 4 | 3.25 | 7000 | 28206 | 1.0 | 1 | 4 | ... | 12 | 3500 | 3500 | 1991 | 0 | 98075 | 47.5928 | -122.086 | 4913 | 14663 |
15668 | 4030100290 | 20141001T000000 | 1680000.0 | 5 | 3.50 | 5170 | 7197 | 3.0 | 1 | 4 | ... | 11 | 3520 | 1650 | 1998 | 0 | 98155 | 47.7561 | -122.271 | 3020 | 12880 |
15692 | 6117502230 | 20141201T000000 | 1637500.0 | 3 | 3.50 | 4660 | 21164 | 2.0 | 1 | 4 | ... | 12 | 4660 | 0 | 1975 | 1990 | 98166 | 47.4418 | -122.354 | 3140 | 24274 |
15828 | 4139420190 | 20150512T000000 | 2480000.0 | 4 | 5.00 | 5310 | 16909 | 1.0 | 0 | 4 | ... | 12 | 3090 | 2220 | 1992 | 0 | 98006 | 47.5515 | -122.113 | 5220 | 15701 |
16260 | 8965510190 | 20140610T000000 | 1250000.0 | 4 | 2.50 | 3700 | 21755 | 1.0 | 0 | 4 | ... | 11 | 2620 | 1080 | 1988 | 0 | 98006 | 47.5662 | -122.108 | 3480 | 13786 |
16817 | 825059178 | 20140923T000000 | 2574000.0 | 4 | 3.75 | 4475 | 20424 | 2.0 | 1 | 4 | ... | 12 | 2659 | 1816 | 1999 | 0 | 98033 | 47.6646 | -122.208 | 4340 | 5250 |
16837 | 4441300170 | 20150112T000000 | 1300000.0 | 4 | 2.50 | 3110 | 11857 | 2.0 | 0 | 4 | ... | 11 | 2040 | 1070 | 1990 | 0 | 98117 | 47.6952 | -122.402 | 3110 | 11570 |
17558 | 7631800015 | 20150407T000000 | 2510000.0 | 3 | 3.25 | 5480 | 57990 | 2.0 | 1 | 4 | ... | 11 | 5480 | 0 | 1991 | 0 | 98166 | 47.4558 | -122.371 | 2500 | 22954 |
18199 | 3625059152 | 20141230T000000 | 3300000.0 | 3 | 3.25 | 4220 | 41300 | 1.0 | 1 | 4 | ... | 11 | 2460 | 1760 | 1958 | 1987 | 98008 | 47.6083 | -122.110 | 3810 | 30401 |
18455 | 8043700300 | 20140608T000000 | 2700000.0 | 4 | 3.25 | 4420 | 7850 | 2.0 | 1 | 4 | ... | 11 | 3150 | 1270 | 2001 | 0 | 98008 | 47.5720 | -122.102 | 2760 | 8525 |
19017 | 2303900100 | 20140911T000000 | 3800000.0 | 3 | 4.25 | 5510 | 35000 | 2.0 | 0 | 4 | ... | 13 | 4910 | 600 | 1997 | 0 | 98177 | 47.7296 | -122.370 | 3430 | 45302 |
20005 | 148000475 | 20140528T000000 | 1400000.0 | 4 | 3.25 | 4700 | 9160 | 1.0 | 0 | 4 | ... | 11 | 2520 | 2180 | 2005 | 0 | 98116 | 47.5744 | -122.406 | 2240 | 8700 |
20325 | 518500480 | 20140811T000000 | 3000000.0 | 3 | 3.50 | 4410 | 10756 | 2.0 | 1 | 4 | ... | 11 | 3430 | 980 | 2014 | 0 | 98056 | 47.5283 | -122.205 | 3550 | 5634 |
20923 | 7852070210 | 20140527T000000 | 1149000.0 | 4 | 3.00 | 5940 | 11533 | 2.0 | 0 | 4 | ... | 11 | 4950 | 990 | 2004 | 0 | 98065 | 47.5443 | -121.870 | 4240 | 12813 |
21050 | 2424059170 | 20150219T000000 | 900000.0 | 5 | 6.00 | 7120 | 40806 | 2.0 | 0 | 4 | ... | 12 | 5480 | 1640 | 2007 | 0 | 98006 | 47.5451 | -122.114 | 3440 | 36859 |
21201 | 518500460 | 20141008T000000 | 2230000.0 | 3 | 3.50 | 3760 | 5634 | 2.0 | 1 | 4 | ... | 11 | 2830 | 930 | 2014 | 0 | 98056 | 47.5285 | -122.205 | 3560 | 5762 |
60 rows × 21 columns
In [182]:
high_quality = houses["grade"] >= 11good_view = houses["view"] == 4smaller = houses["sqft_living"] <= 3000houses[high_quality & good_view & smaller]
Out[182]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
4013 | 724069059 | 20140509T000000 | 2400000.0 | 3 | 2.25 | 3000 | 11665 | 1.5 | 1 | 4 | ... | 11 | 3000 | 0 | 2001 | 0 | 98075 | 47.5884 | -122.086 | 3000 | 15959 |
1 rows × 21 columns
In [196]:
houses[houses["yr_built"] >= 2014]houses[houses["yr_renovated"] >= 2014]houses[(houses["yr_built"] >= 2014) | (houses["yr_renovated"] >= 2014)]
Out[196]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
42 | 7203220400 | 20140707T000000 | 861990.0 | 5 | 2.75 | 3595 | 5639 | 2.0 | 0 | 0 | ... | 9 | 3595 | 0 | 2014 | 0 | 98053 | 47.6848 | -122.016 | 3625 | 5639 |
63 | 9528102996 | 20141207T000000 | 549000.0 | 3 | 1.75 | 1540 | 1044 | 3.0 | 0 | 0 | ... | 8 | 1540 | 0 | 2014 | 0 | 98115 | 47.6765 | -122.320 | 1580 | 3090 |
133 | 8929000270 | 20140512T000000 | 453246.0 | 3 | 2.50 | 2010 | 2287 | 2.0 | 0 | 0 | ... | 8 | 1390 | 620 | 2014 | 0 | 98029 | 47.5517 | -121.998 | 1690 | 1662 |
139 | 2767603505 | 20140507T000000 | 519950.0 | 3 | 2.25 | 1170 | 1249 | 3.0 | 0 | 0 | ... | 8 | 1170 | 0 | 2014 | 0 | 98107 | 47.6722 | -122.381 | 1350 | 1310 |
211 | 1025049114 | 20140717T000000 | 625504.0 | 3 | 2.25 | 1270 | 1566 | 2.0 | 0 | 0 | ... | 8 | 1060 | 210 | 2014 | 0 | 98105 | 47.6647 | -122.284 | 1160 | 1327 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
21598 | 8956200760 | 20141013T000000 | 541800.0 | 4 | 2.50 | 3118 | 7866 | 2.0 | 0 | 2 | ... | 9 | 3118 | 0 | 2014 | 0 | 98001 | 47.2931 | -122.264 | 2673 | 6500 |
21602 | 844000965 | 20140626T000000 | 224000.0 | 3 | 1.75 | 1500 | 11968 | 1.0 | 0 | 0 | ... | 6 | 1500 | 0 | 2014 | 0 | 98010 | 47.3095 | -122.002 | 1320 | 11303 |
21604 | 9834201367 | 20150126T000000 | 429000.0 | 3 | 2.00 | 1490 | 1126 | 3.0 | 0 | 0 | ... | 8 | 1490 | 0 | 2014 | 0 | 98144 | 47.5699 | -122.288 | 1400 | 1230 |
21605 | 3448900210 | 20141014T000000 | 610685.0 | 4 | 2.50 | 2520 | 6023 | 2.0 | 0 | 0 | ... | 9 | 2520 | 0 | 2014 | 0 | 98056 | 47.5137 | -122.167 | 2520 | 6023 |
21609 | 6600060120 | 20150223T000000 | 400000.0 | 4 | 2.50 | 2310 | 5813 | 2.0 | 0 | 0 | ... | 8 | 2310 | 0 | 2014 | 0 | 98146 | 47.5107 | -122.362 | 1830 | 7200 |
704 rows × 21 columns
In [209]:
netflix[netflix["director"] == "David Fincher"]netflix[netflix["director"] == "Martin Scorsese"]netflix[(netflix["director"] == "David Fincher") | (netflix["director"] == "Martin Scorsese")]netflix[netflix["director"].isin(["David Fincher", "Martin Scorsese"])]
Out[209]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
600 | s601 | Movie | The Game | David Fincher | Michael Douglas, Sean Penn, Deborah Kara Unger... | United States | July 1, 2021 | 1997 | R | 129 min | Thrillers | An aloof investment banker's life spirals into... |
1358 | s1359 | Movie | Shutter Island | Martin Scorsese | Leonardo DiCaprio, Mark Ruffalo, Ben Kingsley,... | United States | February 1, 2021 | 2010 | R | 139 min | Thrillers | A U.S. marshal's troubling visions compromise ... |
1595 | s1596 | Movie | MANK | David Fincher | Gary Oldman, Amanda Seyfried, Charles Dance, L... | United States | December 4, 2020 | 2020 | R | 133 min | Dramas, Independent Movies | 1930s Hollywood is reevaluated through the eye... |
2632 | s2633 | Movie | No Direction Home: Bob Dylan | Martin Scorsese | Bob Dylan, Joan Baez, Dave Van Ronk, Peter Yar... | United Kingdom, United States, Japan | April 25, 2020 | 2005 | TV-MA | 208 min | Documentaries, Music & Musicals | Featuring rare concert footage and interviews ... |
2860 | s2861 | Movie | Hugo | Martin Scorsese | Ben Kingsley, Sacha Baron Cohen, Asa Butterfie... | United Kingdom, United States, France | March 1, 2020 | 2011 | PG | 127 min | Children & Family Movies, Dramas | Living inside a Paris train station, an orphan... |
3227 | s3228 | Movie | The Irishman | Martin Scorsese | Robert De Niro, Al Pacino, Joe Pesci, Harvey K... | United States | November 27, 2019 | 2019 | R | 209 min | Dramas | Hit man Frank Sheeran looks back at the secret... |
3759 | s3760 | Movie | Rolling Thunder Revue: A Bob Dylan Story by Ma... | Martin Scorsese | Bob Dylan, Allen Ginsberg, Joan Baez, Patti Sm... | United States | June 12, 2019 | 2019 | TV-MA | 142 min | Documentaries, Music & Musicals | In an alchemic mix of fact and fantasy, Martin... |
6111 | s6112 | Movie | Alice Doesn't Live Here Anymore | Martin Scorsese | Ellen Burstyn, Kris Kristofferson, Billy Green... | United States | July 1, 2019 | 1974 | PG | 112 min | Classic Movies, Comedies, Dramas | A widowed singer and single mother starts over... |
6826 | s6827 | Movie | Gangs of New York | Martin Scorsese | Leonardo DiCaprio, Daniel Day-Lewis, Cameron D... | United States, Italy | August 20, 2019 | 2002 | R | 167 min | Dramas | In the crime-ridden slums of New York in the 1... |
6880 | s6881 | Movie | GoodFellas | Martin Scorsese | Robert De Niro, Ray Liotta, Joe Pesci, Lorrain... | United States | January 1, 2021 | 1990 | R | 145 min | Classic Movies, Dramas | Former mobster Henry Hill recounts his colorfu... |
7431 | s7432 | Movie | Mean Streets | Martin Scorsese | Robert De Niro, Harvey Keitel, David Proval, A... | United States | July 1, 2019 | 1973 | R | 112 min | Classic Movies, Dramas, Independent Movies | In New York's Little Italy, a low-level hoodlu... |
7701 | s7702 | Movie | Panic Room | David Fincher | Jodie Foster, Forest Whitaker, Dwight Yoakam, ... | United States | August 1, 2019 | 2002 | R | 112 min | Thrillers | A woman and her daughter are caught in a game ... |
7820 | s7821 | Movie | Raging Bull | Martin Scorsese | Robert De Niro, Cathy Moriarty, Joe Pesci, Fra... | United States | October 1, 2019 | 1980 | R | 129 min | Classic Movies, Dramas, Sports Movies | This gritty biopic of brutal boxer Jake LaMott... |
8272 | s8273 | Movie | The Departed | Martin Scorsese | Leonardo DiCaprio, Matt Damon, Jack Nicholson,... | United States, Hong Kong | January 1, 2021 | 2006 | R | 151 min | Dramas, Thrillers | Two rookie Boston cops are sent deep undercove... |
8320 | s8321 | Movie | The Girl with the Dragon Tattoo | David Fincher | Daniel Craig, Rooney Mara, Christopher Plummer... | United States, Sweden, Norway | January 5, 2021 | 2011 | R | 158 min | Dramas, Thrillers | When a young computer hacker is tasked with in... |
8511 | s8512 | Movie | The Social Network | David Fincher | Jesse Eisenberg, Andrew Garfield, Justin Timbe... | United States | April 1, 2020 | 2010 | PG-13 | 121 min | Dramas | Director David Fincher's biographical drama ch... |
8735 | s8736 | Movie | Who's That Knocking at My Door? | Martin Scorsese | Zina Bethune, Harvey Keitel, Anne Collette, Le... | United States | July 1, 2019 | 1967 | R | 90 min | Classic Movies, Dramas, Independent Movies | A woman's revelation that she was once raped s... |
8802 | s8803 | Movie | Zodiac | David Fincher | Mark Ruffalo, Jake Gyllenhaal, Robert Downey J... | United States | November 20, 2019 | 2007 | R | 158 min | Cult Movies, Dramas, Thrillers | A political cartoonist, a crime reporter and a... |
In [213]:
fincher = netflix["director"] == "David Fincher"scorsese = netflix["director"] == "Martin Scorsese"recent = netflix["release_year"] > 2015netflix[(fincher | scorsese) & recent]
Out[213]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
1595 | s1596 | Movie | MANK | David Fincher | Gary Oldman, Amanda Seyfried, Charles Dance, L... | United States | December 4, 2020 | 2020 | R | 133 min | Dramas, Independent Movies | 1930s Hollywood is reevaluated through the eye... |
3227 | s3228 | Movie | The Irishman | Martin Scorsese | Robert De Niro, Al Pacino, Joe Pesci, Harvey K... | United States | November 27, 2019 | 2019 | R | 209 min | Dramas | Hit man Frank Sheeran looks back at the secret... |
3759 | s3760 | Movie | Rolling Thunder Revue: A Bob Dylan Story by Ma... | Martin Scorsese | Bob Dylan, Allen Ginsberg, Joan Baez, Patti Sm... | United States | June 12, 2019 | 2019 | TV-MA | 142 min | Documentaries, Music & Musicals | In an alchemic mix of fact and fantasy, Martin... |
In [246]:
df = titanic.head()women = df.sex == 'female'df[~women]
Out[246]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
1 | 1 | 1 | Allison, Master. Hudson Trevor | male | 0.9167 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | 11 | ? | Montreal, PQ / Chesterville, ON |
3 | 1 | 0 | Allison, Mr. Hudson Joshua Creighton | male | 30 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | ? | 135 | Montreal, PQ / Chesterville, ON |
In [249]:
newly_built = houses["yr_built"] >= 2014newly_renovated = houses["yr_renovated"] >= 2014recent_homes = newly_built | newly_renovatedhouses[recent_homes]houses[~recent_homes]
Out[249]:
id | date | price | bedrooms | bathrooms | sqft_living | sqft_lot | floors | waterfront | view | ... | grade | sqft_above | sqft_basement | yr_built | yr_renovated | zipcode | lat | long | sqft_living15 | sqft_lot15 | |
0 | 7129300520 | 20141013T000000 | 221900.0 | 3 | 1.00 | 1180 | 5650 | 1.0 | 0 | 0 | ... | 7 | 1180 | 0 | 1955 | 0 | 98178 | 47.5112 | -122.257 | 1340 | 5650 |
1 | 6414100192 | 20141209T000000 | 538000.0 | 3 | 2.25 | 2570 | 7242 | 2.0 | 0 | 0 | ... | 7 | 2170 | 400 | 1951 | 1991 | 98125 | 47.7210 | -122.319 | 1690 | 7639 |
2 | 5631500400 | 20150225T000000 | 180000.0 | 2 | 1.00 | 770 | 10000 | 1.0 | 0 | 0 | ... | 6 | 770 | 0 | 1933 | 0 | 98028 | 47.7379 | -122.233 | 2720 | 8062 |
3 | 2487200875 | 20141209T000000 | 604000.0 | 4 | 3.00 | 1960 | 5000 | 1.0 | 0 | 0 | ... | 7 | 1050 | 910 | 1965 | 0 | 98136 | 47.5208 | -122.393 | 1360 | 5000 |
4 | 1954400510 | 20150218T000000 | 510000.0 | 3 | 2.00 | 1680 | 8080 | 1.0 | 0 | 0 | ... | 8 | 1680 | 0 | 1987 | 0 | 98074 | 47.6168 | -122.045 | 1800 | 7503 |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
21607 | 2997800021 | 20150219T000000 | 475000.0 | 3 | 2.50 | 1310 | 1294 | 2.0 | 0 | 0 | ... | 8 | 1180 | 130 | 2008 | 0 | 98116 | 47.5773 | -122.409 | 1330 | 1265 |
21608 | 263000018 | 20140521T000000 | 360000.0 | 3 | 2.50 | 1530 | 1131 | 3.0 | 0 | 0 | ... | 8 | 1530 | 0 | 2009 | 0 | 98103 | 47.6993 | -122.346 | 1530 | 1509 |
21610 | 1523300141 | 20140623T000000 | 402101.0 | 2 | 0.75 | 1020 | 1350 | 2.0 | 0 | 0 | ... | 7 | 1020 | 0 | 2009 | 0 | 98144 | 47.5944 | -122.299 | 1020 | 2007 |
21611 | 291310100 | 20150116T000000 | 400000.0 | 3 | 2.50 | 1600 | 2388 | 2.0 | 0 | 0 | ... | 8 | 1600 | 0 | 2004 | 0 | 98027 | 47.5345 | -122.069 | 1410 | 1287 |
21612 | 1523300157 | 20141015T000000 | 325000.0 | 2 | 0.75 | 1020 | 1076 | 2.0 | 0 | 0 | ... | 7 | 1020 | 0 | 2008 | 0 | 98144 | 47.5941 | -122.299 | 1020 | 1357 |
20909 rows × 21 columns
In [258]:
titanic[titanic.survived == 0]titanic[~(titanic.survived == 0)]
Out[258]:
pclass | survived | name | sex | age | sibsp | parch | ticket | fare | cabin | embarked | boat | body | home.dest | |
0 | 1 | 1 | Allen, Miss. Elisabeth Walton | female | 29 | 0 | 0 | 24160 | 211.3375 | B5 | S | 2 | ? | St Louis, MO |
1 | 1 | 1 | Allison, Master. Hudson Trevor | male | 0.9167 | 1 | 2 | 113781 | 151.55 | C22 C26 | S | 11 | ? | Montreal, PQ / Chesterville, ON |
5 | 1 | 1 | Anderson, Mr. Harry | male | 48 | 0 | 0 | 19952 | 26.55 | E12 | S | 3 | ? | New York, NY |
6 | 1 | 1 | Andrews, Miss. Kornelia Theodosia | female | 63 | 1 | 0 | 13502 | 77.9583 | D7 | S | 10 | ? | Hudson, NY |
8 | 1 | 1 | Appleton, Mrs. Edward Dale (Charlotte Lamson) | female | 53 | 2 | 0 | 11769 | 51.4792 | C101 | S | D | ? | Bayside, Queens, NY |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
1261 | 3 | 1 | Turkula, Mrs. (Hedwig) | female | 63 | 0 | 0 | 4134 | 9.5875 | ? | S | 15 | ? | ? |
1277 | 3 | 1 | Vartanian, Mr. David | male | 22 | 0 | 0 | 2658 | 7.225 | ? | C | 13 15 | ? | ? |
1286 | 3 | 1 | Whabee, Mrs. George Joseph (Shawneene Abi-Saab) | female | 38 | 0 | 0 | 2688 | 7.2292 | ? | C | C | ? | ? |
1290 | 3 | 1 | Wilkes, Mrs. James (Ellen Needs) | female | 47 | 1 | 0 | 363272 | 7 | ? | S | ? | ? | ? |
1300 | 3 | 1 | Yasbeck, Mrs. Antoni (Selini Alexander) | female | 15 | 1 | 0 | 2659 | 14.4542 | ? | C | ? | ? | ? |
500 rows × 14 columns
In [260]:
netflix.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 8807 entries, 0 to 8806
Data columns (total 12 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 show_id 8807 non-null object
1 type 8807 non-null object
2 title 8807 non-null object
3 director 6173 non-null object
4 cast 7982 non-null object
5 country 7976 non-null object
6 date_added 8797 non-null object
7 release_year 8807 non-null int64
8 rating 8803 non-null object
9 duration 8804 non-null object
10 listed_in 8807 non-null object
11 description 8807 non-null object
dtypes: int64(1), object(11)
memory usage: 894.5+ KB
In [263]:
netflix[netflix["director"].isna()]
Out[263]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
1 | s2 | TV Show | Blood & Water | NaN | Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban... | South Africa | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, TV Dramas, TV Mysteries | After crossing paths at a party, a Cape Town t... |
3 | s4 | TV Show | Jailbirds New Orleans | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Docuseries, Reality TV | Feuds, flirtations and toilet talk go down amo... |
4 | s5 | TV Show | Kota Factory | NaN | Mayur More, Jitendra Kumar, Ranjan Raj, Alam K... | India | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, Romantic TV Shows, TV ... | In a city of coaching centers known to train I... |
10 | s11 | TV Show | Vendetta: Truth, Lies and The Mafia | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Crime TV Shows, Docuseries, International TV S... | Sicily boasts a bold "Anti-Mafia" coalition. B... |
14 | s15 | TV Show | Crime Stories: India Detectives | NaN | NaN | NaN | September 22, 2021 | 2021 | TV-MA | 1 Season | British TV Shows, Crime TV Shows, Docuseries | Cameras following Bengaluru police on the job ... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
8795 | s8796 | TV Show | Yu-Gi-Oh! Arc-V | NaN | Mike Liscio, Emily Bauer, Billy Bob Thompson, ... | Japan, Canada | May 1, 2018 | 2015 | TV-Y7 | 2 Seasons | Anime Series, Kids' TV | Now that he's discovered the Pendulum Summonin... |
8796 | s8797 | TV Show | Yunus Emre | NaN | Gökhan Atalay, Payidar Tüfekçioglu, Baran Akbu... | Turkey | January 17, 2017 | 2016 | TV-PG | 2 Seasons | International TV Shows, TV Dramas | During the Mongol invasions, Yunus Emre leaves... |
8797 | s8798 | TV Show | Zak Storm | NaN | Michael Johnston, Jessica Gee-George, Christin... | United States, France, South Korea, Indonesia | September 13, 2018 | 2016 | TV-Y7 | 3 Seasons | Kids' TV | Teen surfer Zak Storm is mysteriously transpor... |
8800 | s8801 | TV Show | Zindagi Gulzar Hai | NaN | Sanam Saeed, Fawad Khan, Ayesha Omer, Mehreen ... | Pakistan | December 15, 2016 | 2012 | TV-PG | 1 Season | International TV Shows, Romantic TV Shows, TV ... | Strong-willed, middle-class Kashaf and carefre... |
8803 | s8804 | TV Show | Zombie Dumb | NaN | NaN | NaN | July 1, 2019 | 2018 | TV-Y7 | 2 Seasons | Kids' TV, Korean TV Shows, TV Comedies | While living alone in a spooky town, a young g... |
2634 rows × 12 columns
In [264]:
netflix[netflix["director"].isna() & netflix["cast"].isna()]
Out[264]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
3 | s4 | TV Show | Jailbirds New Orleans | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Docuseries, Reality TV | Feuds, flirtations and toilet talk go down amo... |
10 | s11 | TV Show | Vendetta: Truth, Lies and The Mafia | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Crime TV Shows, Docuseries, International TV S... | Sicily boasts a bold "Anti-Mafia" coalition. B... |
14 | s15 | TV Show | Crime Stories: India Detectives | NaN | NaN | NaN | September 22, 2021 | 2021 | TV-MA | 1 Season | British TV Shows, Crime TV Shows, Docuseries | Cameras following Bengaluru police on the job ... |
66 | s67 | TV Show | Raja Rasoi Aur Anya Kahaniyan | NaN | NaN | India | September 15, 2021 | 2014 | TV-G | 1 Season | Docuseries, International TV Shows | Explore the history and flavors of regional In... |
69 | s70 | TV Show | Stories by Rabindranath Tagore | NaN | NaN | India | September 15, 2021 | 2015 | TV-PG | 1 Season | International TV Shows, TV Dramas | The writings of Nobel Prize winner Rabindranat... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
8605 | s8606 | TV Show | Top Grier | NaN | NaN | United States | December 31, 2018 | 2018 | TV-MA | 3 Seasons | Reality TV | Social media star Hayes Grier returns to North... |
8609 | s8610 | TV Show | Towies | NaN | NaN | NaN | December 27, 2017 | 2016 | TV-MA | 1 Season | International TV Shows, Reality TV | Australia's toughest tow truck operators work ... |
8700 | s8701 | TV Show | Wartime Portraits | NaN | NaN | Poland | September 15, 2016 | 2014 | TV-MA | 1 Season | Docuseries, International TV Shows | Part live-action and part animation, this visu... |
8755 | s8756 | TV Show | Women Behind Bars | NaN | NaN | United States | November 1, 2016 | 2010 | TV-14 | 3 Seasons | Crime TV Shows, Docuseries | This reality series recounts true stories of w... |
8803 | s8804 | TV Show | Zombie Dumb | NaN | NaN | NaN | July 1, 2019 | 2018 | TV-Y7 | 2 Seasons | Kids' TV, Korean TV Shows, TV Comedies | While living alone in a spooky town, a young g... |
352 rows × 12 columns
In [267]:
netflix[~netflix.director.notna()]
Out[267]:
show_id | type | title | director | cast | country | date_added | release_year | rating | duration | listed_in | description | |
1 | s2 | TV Show | Blood & Water | NaN | Ama Qamata, Khosi Ngema, Gail Mabalane, Thaban... | South Africa | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, TV Dramas, TV Mysteries | After crossing paths at a party, a Cape Town t... |
3 | s4 | TV Show | Jailbirds New Orleans | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Docuseries, Reality TV | Feuds, flirtations and toilet talk go down amo... |
4 | s5 | TV Show | Kota Factory | NaN | Mayur More, Jitendra Kumar, Ranjan Raj, Alam K... | India | September 24, 2021 | 2021 | TV-MA | 2 Seasons | International TV Shows, Romantic TV Shows, TV ... | In a city of coaching centers known to train I... |
10 | s11 | TV Show | Vendetta: Truth, Lies and The Mafia | NaN | NaN | NaN | September 24, 2021 | 2021 | TV-MA | 1 Season | Crime TV Shows, Docuseries, International TV S... | Sicily boasts a bold "Anti-Mafia" coalition. B... |
14 | s15 | TV Show | Crime Stories: India Detectives | NaN | NaN | NaN | September 22, 2021 | 2021 | TV-MA | 1 Season | British TV Shows, Crime TV Shows, Docuseries | Cameras following Bengaluru police on the job ... |
... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
8795 | s8796 | TV Show | Yu-Gi-Oh! Arc-V | NaN | Mike Liscio, Emily Bauer, Billy Bob Thompson, ... | Japan, Canada | May 1, 2018 | 2015 | TV-Y7 | 2 Seasons | Anime Series, Kids' TV | Now that he's discovered the Pendulum Summonin... |
8796 | s8797 | TV Show | Yunus Emre | NaN | Gökhan Atalay, Payidar Tüfekçioglu, Baran Akbu... | Turkey | January 17, 2017 | 2016 | TV-PG | 2 Seasons | International TV Shows, TV Dramas | During the Mongol invasions, Yunus Emre leaves... |
8797 | s8798 | TV Show | Zak Storm | NaN | Michael Johnston, Jessica Gee-George, Christin... | United States, France, South Korea, Indonesia | September 13, 2018 | 2016 | TV-Y7 | 3 Seasons | Kids' TV | Teen surfer Zak Storm is mysteriously transpor... |
8800 | s8801 | TV Show | Zindagi Gulzar Hai | NaN | Sanam Saeed, Fawad Khan, Ayesha Omer, Mehreen ... | Pakistan | December 15, 2016 | 2012 | TV-PG | 1 Season | International TV Shows, Romantic TV Shows, TV ... | Strong-willed, middle-class Kashaf and carefre... |
8803 | s8804 | TV Show | Zombie Dumb | NaN | NaN | NaN | July 1, 2019 | 2018 | TV-Y7 | 2 Seasons | Kids' TV, Korean TV Shows, TV Comedies | While living alone in a spooky town, a young g... |
2634 rows × 12 columns
In [293]:
titanic[titanic["sex"] == "female"].survived.value_counts()
Out[293]:
1 339
0 127
Name: survived, dtype: int64
In [294]:
titanic[titanic["sex"] == "male"].survived.value_counts()
Out[294]:
0 682
1 161
Name: survived, dtype: int64
In [299]:
women = titanic["sex"] == "female"titanic[women].survived.value_counts().plot(kind="pie")
Out[299]:
<AxesSubplot:ylabel='survived'>
In [300]:
titanic[~women].survived.value_counts().plot(kind="pie")
Out[300]:
<AxesSubplot:ylabel='survived'>
In [305]:
houses[houses["price"] > 3000000].zipcode.value_counts().plot(kind="bar")
Out[305]:
<AxesSubplot:>
In [307]:
houses.zipcode.value_counts().head(10).plot(kind="bar")
Out[307]:
<AxesSubplot:>
